| # | School | Team | Rec. | |
|---|---|---|---|---|
| 1 |  |
University of Washington | Huskies 1 | 5–2 |
| 2 | |
University of Washington | Huskies 2 | 4–3 |
| 3 |  |
Western Washington University | Vikings 2 | 3–4 |
| 4 | |
Western Washington University | Vikings 1 | 1–6 |
| 5 | |
Western Washington University | Vikings 3 | 1–6 |
| 6 | |
Western Washington University | Vikings 5 | 1–6 |
| 7 | |
University of Washington | Huskies 3 | 0–0 |
| 8 | |
Western Washington University | Vikings 4 | 0–0 |
Each side is the sum of its three boats (the skipper's fleet rating times 0.72 plus a team race offset learned from their past matches, plus the crew's offset and a small experience term) plus the school's team race strength and a home-water edge for the host. The win probability is a logistic function of the difference. The forecast was made before the event: the model was refitted on every match sailed before the first day, with fleet ratings as of the week before.
Fitted on the 9,566 team race matches sailed before 2018-03-03, using the line-ups that actually raced. It called 18 of 21 matches (86%) with a log-loss of 0.410 (a coin flip scores 0.693), so the event went well for the forecast. Orderliness −0.01 ± 0.38: a typical event, more orderly than 40% of college team race events (temperature of the forecast log-odds that best fits the results, relative to the league average; nothing about the field, venue or wind predicts it, see the Weather tab). vs forecast is a team's wins minus the wins the model expected from the matches it sailed: positive means it beat its rating.
For each side, the performance strength is the value that would have made its record least surprising: the strength at which the model's expected wins over exactly these opponents equal the actual wins, with every opponent fixed at its pre-event strength. For a skipper, the same shift is applied only to their boat in the matches they sailed, with team-mates and opponents fixed; team-mates who sailed every match together therefore get the same number. Surprise is in bits: -log2 of the probability of the record at the pre-event strength minus the same at the performance strength. P(this good or better) treats matches as independent coin flips at the model's pre-event probabilities, so it ignores form within the day; read it as a rough guide.
Pre-event strength against the strength that would have made each record least surprising, everything else fixed. Δ is in the model's logit units, the same scale as the boat values above (a side is three boats plus the school term); green is a clear over-performance, red a clear under-performance. Skippers need three or more matches.
| Place | School | Strength | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| 1 | University of Washington Huskies 1 | 6.11 | 9.11 | 6–0 | 5.3 | ≥+3.00 | 1.1 | 46% |
| 3 | Western Washington University Vikings 2 | 2.78 | 5.13 | 4–2 | 1.8 | +2.35 | 3.7 | 3% |
| 2 | University of Washington Huskies 2 | 5.07 | 5.92 | 5–1 | 4.4 | +0.85 | 0.3 | 47% |
| 5 | Western Washington University Vikings 3 | 3.60 | 3.74 | 3–3 | 2.9 | +0.15 | 0.0 | 67% |
| 7 | University of Washington Huskies 3 | 2.39 | 1.68 | 1–5 | 1.5 | −0.70 | 0.2 | 89% |
| 4 | Western Washington University Vikings 1 | 5.04 | 2.62 | 2–4 | 4.3 | −2.43 | 4.2 | >99% |
| 8 | Western Washington University Vikings 4 | 1.72 | -1.28 | 0–6 | 0.7 | ≤−3.00 | 1.1 | >99% |
| Skipper | School | Value | Perf. | Record | Exp. wins | Δ | Surprise (bits) | P(this good or better) |
|---|---|---|---|---|---|---|---|---|
| Dillon Kilroy | Western Washington University | 1.11 | 3.46 | 4–2 | 1.8 | +2.35 | 3.7 | 3% |
| Chandler Sharp | Western Washington University | 0.60 | 2.94 | 4–2 | 1.8 | +2.35 | 3.7 | 3% |
| Spencer Shear | Western Washington University | -0.07 | 2.27 | 4–2 | 1.8 | +2.35 | 3.7 | 3% |
| Austin Hauter | University of Washington | 1.64 | 2.49 | 5–1 | 4.4 | +0.85 | 0.3 | 47% |
| Carter Erickson | Western Washington University | 0.70 | 0.85 | 3–3 | 2.9 | +0.15 | 0.0 | 67% |
| Nikoline Alden | Western Washington University | 0.37 | 0.51 | 3–3 | 2.9 | +0.15 | 0.0 | 67% |
| Nathaniel Gordon | University of Washington | 1.54 | 0.83 | 1–5 | 1.5 | −0.70 | 0.2 | 89% |
| Yinjin Maile | University of Washington | 0.21 | -0.49 | 1–5 | 1.5 | −0.70 | 0.2 | 89% |
| Ezekiel Ward | Western Washington University | 1.02 | -1.40 | 2–4 | 4.3 | −2.43 | 4.2 | >99% |
| Carter Dojan | Western Washington University | -0.07 | -3.07 | 0–6 | 0.7 | ≤−3.00 | 1.1 | >99% |
| Benjamin Morasch | Western Washington University | 0.09 | -2.91 | 0–6 | 0.7 | ≤−3.00 | 1.1 | >99% |
| Audrey Prewitt | Western Washington University | 0.52 | -2.48 | 0–6 | 0.7 | ≤−3.00 | 1.1 | >99% |
Probability the model gave the side that went on to win. Red bars are upsets (the winner was given under 50%).
| Team | Rec. | 1 | 2 | 2 | 1 | 3 | 5 | 3 | 4 | |
|---|---|---|---|---|---|---|---|---|---|---|
| University of Washington Huskies 1 | 14–7 | ✕ | ✕ | W | W | W | W | ✕ | W |
| University of Washington Huskies 2 | 14–7 | ✕ | ✕ | W | W | W | W | ✕ | W |
| Western Washington University Vikings 2 | 14–21 | L | L | ✕ | ✕ | ✕ | ✕ | L | ✕ |
| Western Washington University Vikings 1 | 14–21 | L | L | ✕ | ✕ | ✕ | ✕ | L | ✕ |
| Western Washington University Vikings 3 | 14–21 | L | L | ✕ | ✕ | ✕ | ✕ | L | ✕ |
| Western Washington University Vikings 5 | 14–21 | L | L | ✕ | ✕ | ✕ | ✕ | L | ✕ |
| University of Washington Huskies 3 | 14–7 | ✕ | ✕ | W | W | W | W | ✕ | W |
| Western Washington University Vikings 4 | 14–21 | L | L | ✕ | ✕ | ✕ | ✕ | L | ✕ |
| # | Winner | Loser | Pos. | ||||
|---|---|---|---|---|---|---|---|
| 1 | |
Huskies 1 | 1-2-5 | def. | |
Vikings 1 | 3-4-6 |
| 2 | |
Huskies 2 | 2-3-5 | def. | |
Vikings 2 | 1-4-6 |
| 3 | |
Vikings 3 | 1-2-5 | def. | |
Huskies 3 | 3-4-6 |
| 4 | |
Vikings 5 | 1-2-3 | def. | |
Vikings 4 | 4-5-6 |
| 5 | |
Huskies 2 | 2-3-5 | def. | |
Vikings 1 | 1-4-6 |
| 6 | |
Vikings 2 | 1-3-5 | def. | |
Huskies 3 | 2-4-6 |
| 7 | |
Huskies 1 | 1-2-3 | def. | |
Vikings 5 | 4-5-6 |
| 8 | |
Vikings 3 | 1-2-6 | def. | |
Vikings 4 | 3-4-5 |
| 9 | |
Vikings 2 | 1-4-5 | def. | |
Vikings 5 | 2-3-6 |
| 10 | |
Huskies 2 | 1-2-3 | def. | |
Huskies 3 | 4-5-6 |
| 11 | |
Huskies 3 | 1-2-3 | def. | |
Vikings 4 | 4-5-6 |
| 12 | |
Huskies 2 | 1-2-5 | def. | |
Vikings 3 | 3-4-6 |
| 13 | |
Huskies 1 | 1-2-5 | def. | |
Huskies 3 | 3-4-6 |
| 14 | |
Vikings 5 | 1-2-6 | def. | |
Vikings 3 | 3-4-5 |
| 15 | |
Huskies 1 | 1-2-5 | def. | |
Vikings 4 | 3-4-6 |
| 16 | |
Vikings 5 | 1-3-6 | def. | |
Huskies 3 | 2-4-5 |
| 17 | |
Vikings 1 | 1-2-4 | def. | |
Huskies 3 | 3-5-6 |
| 18 | |
Vikings 2 | 1-2-5 | def. | |
Vikings 3 | 3-4-6 |
| 19 | |
Vikings 1 | 1-2-4 | def. | |
Vikings 4 | 3-5-6 |
| 20 | |
Huskies 1 | 1-2-6 | def. | |
Huskies 2 | 3-4-5 |
| 21 | |
Vikings 3 | 2-3-4 | def. | |
Vikings 1 | 1-5-6 |
| 22 | |
Huskies 2 | 1-2-6 | def. | |
Vikings 5 | 3-4-5 |
| 23 | |
Vikings 2 | 2-3-5 | def. | |
Vikings 1 | 1-4-6 |
| 24 | |
Vikings 2 | 1-3-4 | def. | |
Vikings 4 | 2-5-6 |
| 25 | |
Huskies 1 | 1-2-3 | def. | |
Vikings 3 | 4-5-6 |
| 26 | |
Vikings 1 | 1-2-4 | def. | |
Vikings 5 | 3-5-6 |
| 27 | |
Huskies 2 | 1-2-5 | def. | |
Vikings 4 | 3-4-6 |
| 28 | |
Huskies 1 | 1-2-4 | def. | |
Vikings 2 | 3-5-6 |
Orderliness is how tightly a fleet race’s finishing order follows the pre-regatta ratings, relative to a typical event (0): positive is the favourites’ day, negative the underdogs’. A value of ±0.04 means a rating gap counts about 3% less than on a typical day. This event is not a fleet race the rating model scores, so there is no actual value for it: this is what this venue’s fleet racing history says about the breeze on the day, read off the chart at the star. How this is estimated · compare venues.
Short write-ups of what the ratings and results show, with the numbers and how they were computed.
